def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
The bounding box is computed to be as minimal as possible.
EXAMPLES:
An example without an angle::
sage: p = ellipse((-2, 3), 1, 2)
sage: d = p.get_minmax_data()
sage: d['xmin']
-3.0
sage: d['xmax']
-1.0
sage: d['ymin']
1.0
sage: d['ymax']
5.0
The same example with a rotation of angle `\pi/2`::
sage: p = ellipse((-2, 3), 1, 2, pi/2)
sage: d = p.get_minmax_data()
sage: d['xmin']
-4.0
sage: d['xmax']
0.0
sage: d['ymin']
2.0
sage: d['ymax']
4.0
"""
from sage.plot.plot import minmax_data
epsilon = 0.000001
cos_angle = cos(self.angle)
if abs(cos_angle) > 1-epsilon:
xmax = self.r1
ymax = self.r2
elif abs(cos_angle) < epsilon:
xmax = self.r2
ymax = self.r1
else:
sin_angle = sin(self.angle)
tan_angle = sin_angle / cos_angle
sxmax = ((self.r2*tan_angle)/self.r1)**2
symax = (self.r2/(self.r1*tan_angle))**2
xmax = (
abs(self.r1 * cos_angle / sqrt(sxmax+1.)) +
abs(self.r2 * sin_angle / sqrt(1./sxmax+1.)))
ymax = (
abs(self.r1 * sin_angle / sqrt(symax+1.)) +
abs(self.r2 * cos_angle / sqrt(1./symax+1.)))
return minmax_data([self.x - xmax, self.x + xmax],
[self.y - ymax, self.y + ymax],
dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: d = polygon([[1,2], [5,6], [5,0]], rgbcolor=(1,0,1))[0].get_minmax_data()
sage: d['ymin']
0.0
sage: d['xmin']
1.0
::
sage: d = point((3, 3), rgbcolor=hue(0.75))[0].get_minmax_data()
sage: d['xmin']
3.0
sage: d['ymin']
3.0
::
sage: l = line([(100, 100), (120, 120)])[0]
sage: d = l.get_minmax_data()
sage: d['xmin']
100.0
sage: d['xmax']
120.0
"""
from sage.plot.plot import minmax_data
return minmax_data(self.xdata, self.ydata, dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: b = bar_chart([-2.3,5,-6,12])
sage: d = b.get_minmax_data()
sage: d['xmin']
0
sage: d['xmax']
4
"""
return minmax_data([0, len(self.datalist)], self.datalist, dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: x,y = var('x,y')
sage: d = plot_vector_field((.01*x,x+y), (x,10,20), (y,10,20))[0].get_minmax_data()
sage: d['xmin']
10.0
sage: d['ymin']
10.0
"""
from sage.plot.plot import minmax_data
return minmax_data(self.xpos_array, self.ypos_array, dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: x,y = var('x,y')
sage: d = plot_vector_field((.01*x,x+y), (x,10,20), (y,10,20))[0].get_minmax_data()
sage: d['xmin']
10.0
sage: d['ymin']
10.0
"""
from sage.plot.plot import minmax_data
return minmax_data(self.xpos_array, self.ypos_array, dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data. Notice
that, for text, the box is just the location itself.
EXAMPLES::
sage: T = text("Where am I?",(1,1))
sage: t=T[0]
sage: t.get_minmax_data()['ymin']
1.0
sage: t.get_minmax_data()['ymax']
1.0
"""
from sage.plot.plot import minmax_data
return minmax_data([self.x], [self.y], dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data. Notice
that, for text, the box is just the location itself.
EXAMPLES::
sage: T = text("Where am I?",(1,1))
sage: t=T[0]
sage: t.get_minmax_data()['ymin']
1.0
sage: t.get_minmax_data()['ymax']
1.0
"""
from sage.plot.plot import minmax_data
return minmax_data([self.x], [self.y], dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: x,y = var('x,y')
sage: f(x, y) = x^2 + y^2
sage: d = density_plot(f, (3, 6), (3, 6))[0].get_minmax_data()
sage: d['xmin']
3.0
sage: d['ymin']
3.0
"""
from sage.plot.plot import minmax_data
return minmax_data(self.xrange, self.yrange, dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: x,y = var('x,y')
sage: f(x, y) = x^2 + y^2
sage: d = density_plot(f, (3, 6), (3, 6))[0].get_minmax_data()
sage: d['xmin']
3.0
sage: d['ymin']
3.0
"""
from sage.plot.plot import minmax_data
return minmax_data(self.xrange, self.yrange, dict=True)
def get_minmax_data(self):
"""
Get minimum and maximum horizontal and vertical ranges
for the Histogram object.
EXAMPLES::
sage: H = histogram([10,3,5], normed=True); h = H[0]
sage: h.get_minmax_data()
{'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.4761904761904765, 'ymin': 0}
sage: G = histogram([random() for _ in range(500)]); g = G[0]
sage: g.get_minmax_data() # random output
{'xmax': 0.99729312925213209, 'xmin': 0.00013024562219410285, 'ymax': 61, 'ymin': 0}
sage: Y = histogram([random()*10 for _ in range(500)], range=[2,8]); y = Y[0]
sage: ymm = y.get_minmax_data(); ymm['xmax'], ymm['xmin']
(8.0, 2.0)
sage: Z = histogram([[1,3,2,0], [4,4,3,3]]); z = Z[0]
sage: z.get_minmax_data()
{'xmax': 4.0, 'xmin': 0, 'ymax': 2, 'ymin': 0}
"""
import numpy
options = self.options()
opt = dict(range=options.pop('range', None),
bins=options.pop('bins', None),
normed=options.pop('normed', None),
weights=options.pop('weights', None))
#check to see if a list of datasets
if not hasattr(self.datalist[0], '__contains__'):
ydata, xdata = numpy.histogram(self.datalist, **opt)
return minmax_data(xdata, [0] + list(ydata), dict=True)
else:
m = {'xmax': 0, 'xmin': 0, 'ymax': 0, 'ymin': 0}
if not options.pop('stacked', None):
for d in self.datalist:
ydata, xdata = numpy.histogram(d, **opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = max([m['ymax']] + list(ydata))
return m
else:
for d in self.datalist:
ydata, xdata = numpy.histogram(d, **opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = m['ymax'] + max(list(ydata))
return m
def get_minmax_data(self):
"""
Get minimum and maximum horizontal and vertical ranges
for the Histogram object.
EXAMPLES::
sage: H = histogram([10,3,5], normed=True); h = H[0]
sage: h.get_minmax_data()
{'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.4761904761904765, 'ymin': 0}
sage: G = histogram([random() for _ in range(500)]); g = G[0]
sage: g.get_minmax_data() # random output
{'xmax': 0.99729312925213209, 'xmin': 0.00013024562219410285, 'ymax': 61, 'ymin': 0}
sage: Y = histogram([random()*10 for _ in range(500)], range=[2,8]); y = Y[0]
sage: ymm = y.get_minmax_data(); ymm['xmax'], ymm['xmin']
(8.0, 2.0)
sage: Z = histogram([[1,3,2,0], [4,4,3,3]]); z = Z[0]
sage: z.get_minmax_data()
{'xmax': 4.0, 'xmin': 0, 'ymax': 2, 'ymin': 0}
"""
import numpy
options=self.options()
opt=dict(range = options.pop('range',None),
bins = options.pop('bins',None),
normed = options.pop('normed',None),
weights = options.pop('weights', None))
#check to see if a list of datasets
if not hasattr(self.datalist[0],'__contains__' ):
ydata,xdata=numpy.histogram(self.datalist, **opt)
return minmax_data(xdata,[0]+list(ydata), dict=True)
else:
m = { 'xmax': 0, 'xmin':0, 'ymax':0, 'ymin':0}
if not options.pop('stacked',None):
for d in self.datalist:
ydata, xdata = numpy.histogram(d,**opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = max([m['ymax']] + list(ydata))
return m
else:
for d in self.datalist:
ydata, xdata = numpy.histogram(d,**opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = m['ymax'] + max(list(ydata))
return m
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: p = circle((3, 3), 1)
sage: d = p.get_minmax_data()
sage: d['xmin']
2.0
sage: d['ymin']
2.0
"""
from sage.plot.plot import minmax_data
return minmax_data([self.x - self.r, self.x + self.r],
[self.y - self.r, self.y + self.r],
dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: p = circle((3, 3), 1)
sage: d = p.get_minmax_data()
sage: d['xmin']
2.0
sage: d['ymin']
2.0
"""
from sage.plot.plot import minmax_data
return minmax_data([self.x - self.r, self.x + self.r],
[self.y - self.r, self.y + self.r],
dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: m = matrix_plot(matrix([[1,3,5,1],[2,4,5,6],[1,3,5,7]]))[0]
sage: list(sorted(m.get_minmax_data().items()))
[('xmax', 3.5), ('xmin', -0.5), ('ymax', 2.5), ('ymin', -0.5)]
"""
from sage.plot.plot import minmax_data
limits = minmax_data(self.xrange, self.yrange, dict=True)
# center the matrix so that, for example, the square representing the
# (0,0) entry is centered on the origin.
for k, v in limits.iteritems():
limits[k] -= 0.5
return limits
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: D = disk((5,4), 1, (pi/2, pi))
sage: d = D.get_minmax_data()
sage: d['xmin']
4.0
sage: d['ymin']
3.0
sage: d['xmax']
6.0
sage: d['ymax']
5.0
"""
from sage.plot.plot import minmax_data
return minmax_data([self.x - self.r, self.x + self.r], [self.y - self.r, self.y + self.r], dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: m = matrix_plot(matrix([[1,3,5,1],[2,4,5,6],[1,3,5,7]]))[0]
sage: list(sorted(m.get_minmax_data().items()))
[('xmax', 3.5), ('xmin', -0.5), ('ymax', -0.5), ('ymin', 2.5)]
"""
from sage.plot.plot import minmax_data
limits= minmax_data(self.xrange, self.yrange, dict=True)
if self.options()['origin']!='lower':
# flip y-axis so that the picture looks correct.
limits['ymin'],limits['ymax']=limits['ymax'],limits['ymin']
# center the matrix so that, for example, the square representing the
# (0,0) entry is centered on the origin.
for k,v in limits.iteritems():
limits[k]-=0.5
return limits
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: D = disk((5,4), 1, (pi/2, pi))
sage: d = D.get_minmax_data()
sage: d['xmin']
4.0
sage: d['ymin']
3.0
sage: d['xmax']
6.0
sage: d['ymax']
5.0
"""
from sage.plot.plot import minmax_data
return minmax_data([self.x - self.r, self.x + self.r],
[self.y - self.r, self.y + self.r],
dict=True)
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
EXAMPLES::
sage: m = matrix_plot(matrix([[1,3,5,1],[2,4,5,6],[1,3,5,7]]))[0]
sage: list(sorted(m.get_minmax_data().items()))
[('xmax', 3.5), ('xmin', -0.5), ('ymax', -0.5), ('ymin', 2.5)]
"""
from sage.plot.plot import minmax_data
limits= minmax_data(self.xrange, self.yrange, dict=True)
if self.options()['origin']!='lower':
# flip y-axis so that the picture looks correct.
limits['ymin'],limits['ymax']=limits['ymax'],limits['ymin']
# center the matrix so that, for example, the square representing the
# (0,0) entry is centered on the origin.
for k, v in iteritems(limits):
limits[k] -= 0.5
return limits
def get_minmax_data(self):
"""
Get minimum and maximum horizontal and vertical ranges
for the Histogram object.
EXAMPLES::
sage: H = histogram([10,3,5], density=True); h = H[0]
sage: h.get_minmax_data() # rel tol 1e-15
{'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.4761904761904765, 'ymin': 0}
sage: G = histogram([random() for _ in range(500)]); g = G[0]
sage: g.get_minmax_data() # random output
{'xmax': 0.99729312925213209, 'xmin': 0.00013024562219410285, 'ymax': 61, 'ymin': 0}
sage: Y = histogram([random()*10 for _ in range(500)], range=[2,8]); y = Y[0]
sage: ymm = y.get_minmax_data(); ymm['xmax'], ymm['xmin']
(8.0, 2.0)
sage: Z = histogram([[1,3,2,0], [4,4,3,3]]); z = Z[0]
sage: z.get_minmax_data()
{'xmax': 4.0, 'xmin': 0, 'ymax': 2, 'ymin': 0}
TESTS::
sage: h = histogram([10,3,5], normed=True)[0]
sage: h.get_minmax_data() # rel tol 1e-15
{'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.4761904761904765, 'ymin': 0}
"""
import numpy
# Extract these options (if they are not None) and pass them to
# histogram()
options = self.options()
opt = {}
for key in ('range', 'bins', 'normed', 'density', 'weights'):
try:
value = options[key]
except KeyError:
pass
else:
if value is not None:
opt[key] = value
#check to see if a list of datasets
if not hasattr(self.datalist[0], '__contains__'):
ydata, xdata = numpy.histogram(self.datalist, **opt)
return minmax_data(xdata, [0] + list(ydata), dict=True)
else:
m = {'xmax': 0, 'xmin': 0, 'ymax': 0, 'ymin': 0}
if not options.get('stacked'):
for d in self.datalist:
ydata, xdata = numpy.histogram(d, **opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = max([m['ymax']] + list(ydata))
return m
else:
for d in self.datalist:
ydata, xdata = numpy.histogram(d, **opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = m['ymax'] + max(list(ydata))
return m
def get_minmax_data(self):
"""
Get minimum and maximum horizontal and vertical ranges
for the Histogram object.
EXAMPLES::
sage: H = histogram([10,3,5], density=True); h = H[0]
sage: h.get_minmax_data() # rel tol 1e-15
{'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.4761904761904765, 'ymin': 0}
sage: G = histogram([random() for _ in range(500)]); g = G[0]
sage: g.get_minmax_data() # random output
{'xmax': 0.99729312925213209, 'xmin': 0.00013024562219410285, 'ymax': 61, 'ymin': 0}
sage: Y = histogram([random()*10 for _ in range(500)], range=[2,8]); y = Y[0]
sage: ymm = y.get_minmax_data(); ymm['xmax'], ymm['xmin']
(8.0, 2.0)
sage: Z = histogram([[1,3,2,0], [4,4,3,3]]); z = Z[0]
sage: z.get_minmax_data()
{'xmax': 4.0, 'xmin': 0, 'ymax': 2, 'ymin': 0}
TESTS::
sage: h = histogram([10,3,5], normed=True)[0]
doctest:warning...:
DeprecationWarning: the 'normed' option is deprecated. Use 'density' instead.
See https://trac.sagemath.org/25260 for details.
sage: h.get_minmax_data()
doctest:warning ...:
VisibleDeprecationWarning: Passing `normed=True` on non-uniform bins has always been broken, and computes neither the probability density function nor the probability mass function. The result is only correct if the bins are uniform, when density=True will produce the same result anyway. The argument will be removed in a future version of numpy.
{'xmax': 10.0, 'xmin': 3.0, 'ymax': 0.476190476190..., 'ymin': 0}
"""
import numpy
# Extract these options (if they are not None) and pass them to
# histogram()
options = self.options()
opt = {}
for key in ('range', 'bins', 'normed', 'density', 'weights'):
try:
value = options[key]
except KeyError:
pass
else:
if value is not None:
opt[key] = value
#check to see if a list of datasets
if not hasattr(self.datalist[0], '__contains__'):
ydata, xdata = numpy.histogram(self.datalist, **opt)
return minmax_data(xdata, [0] + list(ydata), dict=True)
else:
m = {'xmax': 0, 'xmin': 0, 'ymax': 0, 'ymin': 0}
if not options.get('stacked'):
for d in self.datalist:
ydata, xdata = numpy.histogram(d, **opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = max([m['ymax']] + list(ydata))
return m
else:
for d in self.datalist:
ydata, xdata = numpy.histogram(d, **opt)
m['xmax'] = max([m['xmax']] + list(xdata))
m['xmin'] = min([m['xmin']] + list(xdata))
m['ymax'] = m['ymax'] + max(list(ydata))
return m
def get_minmax_data(self):
"""
Returns a dictionary with the bounding box data.
The bounding box is computed as minimal as possible.
EXAMPLES:
An example without angle::
sage: p = arc((-2, 3), 1, 2)
sage: d = p.get_minmax_data()
sage: d['xmin']
-3.0
sage: d['xmax']
-1.0
sage: d['ymin']
1.0
sage: d['ymax']
5.0
The same example with a rotation of angle `\pi/2`::
sage: p = arc((-2, 3), 1, 2, pi/2)
sage: d = p.get_minmax_data()
sage: d['xmin']
-4.0
sage: d['xmax']
0.0
sage: d['ymin']
2.0
sage: d['ymax']
4.0
"""
from sage.plot.plot import minmax_data
twopi = 2*pi
s1 = self.s1
s2 = self.s2
s = s2-s1
s1 = fmod(s1,twopi)
if s1 < 0: s1 += twopi
s2 = fmod(s1 + s,twopi)
if s2 < 0: s2 += twopi
r1 = self.r1
r2 = self.r2
angle = fmod(self.angle,twopi)
if angle < 0: angle += twopi
epsilon = float(0.0000001)
cos_angle = cos(angle)
sin_angle = sin(angle)
if cos_angle > 1-epsilon:
xmin=-r1; ymin=-r2
xmax=r1; ymax=r2
axmin = pi; axmax = 0
aymin = 3*pi/2; aymax = pi/2
elif cos_angle < -1+epsilon:
xmin=-r1; ymin=-r2
xmax=r1; ymax=r2
axmin=0; axmax=pi
aymin=pi/2; aymax=3*pi/2
elif sin_angle > 1-epsilon:
xmin=-r2; ymin=-r1
xmax=r2; ymax=r1
axmin = pi/2; axmax = 3*pi/2
aymin = pi; aymax = 0
elif sin_angle < -1+epsilon:
xmin=-r2; ymin=-r1
xmax=r2; ymax=r1
axmin = 3*pi/2; axmax = pi/2
aymin = 0; aymax = pi
else:
tan_angle = sin_angle / cos_angle
axmax = atan(-r2/r1*tan_angle)
if axmax < 0: axmax += twopi
xmax = (
r1 * cos_angle * cos(axmax) -
r2 * sin_angle * sin(axmax))
if xmax < 0:
xmax = -xmax
axmax = fmod(axmax+pi,twopi)
xmin = -xmax
axmin = fmod(axmax + pi,twopi)
aymax = atan(r2/(r1*tan_angle))
if aymax < 0: aymax += twopi
ymax = (
r1 * sin_angle * cos(aymax) +
r2 * cos_angle * sin(aymax))
if ymax < 0:
ymax = -ymax
aymax = fmod(aymax+pi,twopi)
ymin = -ymax
aymin = fmod(aymax + pi, twopi)
if s < twopi-epsilon: # bb determined by the sector
def is_cyclic_ordered(x1,x2,x3):
return (
(x1 < x2 and x2 < x3) or
(x2 < x3 and x3 < x1) or
(x3 < x1 and x1 < x2))
x1 = cos_angle*r1*cos(s1) - sin_angle*r2*sin(s1)
x2 = cos_angle*r1*cos(s2) - sin_angle*r2*sin(s2)
y1 = sin_angle*r1*cos(s1) + cos_angle*r2*sin(s1)
y2 = sin_angle*r1*cos(s2) + cos_angle*r2*sin(s2)
if is_cyclic_ordered(s1,s2,axmin): xmin = min(x1,x2)
if is_cyclic_ordered(s1,s2,aymin): ymin = min(y1,y2)
if is_cyclic_ordered(s1,s2,axmax): xmax = max(x1,x2)
if is_cyclic_ordered(s1,s2,aymax): ymax = max(y1,y2)
return minmax_data([self.x + xmin, self.x + xmax],
[self.y + ymin, self.y + ymax],
dict=True)
def get_minmax_data(self):
r"""
Return a dictionary with the bounding box data.
The bounding box is computed as minimal as possible.
EXAMPLES:
An example without angle::
sage: p = arc((-2, 3), 1, 2)
sage: d = p.get_minmax_data()
sage: d['xmin']
-3.0
sage: d['xmax']
-1.0
sage: d['ymin']
1.0
sage: d['ymax']
5.0
The same example with a rotation of angle `\pi/2`::
sage: p = arc((-2, 3), 1, 2, pi/2)
sage: d = p.get_minmax_data()
sage: d['xmin']
-4.0
sage: d['xmax']
0.0
sage: d['ymin']
2.0
sage: d['ymax']
4.0
"""
from sage.plot.plot import minmax_data
twopi = 2 * pi
s1 = self.s1
s2 = self.s2
s = s2 - s1
s1 = fmod(s1, twopi)
if s1 < 0:
s1 += twopi
s2 = fmod(s1 + s, twopi)
if s2 < 0:
s2 += twopi
r1 = self.r1
r2 = self.r2
angle = fmod(self.angle, twopi)
if angle < 0:
angle += twopi
epsilon = float(0.0000001)
cos_angle = cos(angle)
sin_angle = sin(angle)
if cos_angle > 1 - epsilon:
xmin = -r1
ymin = -r2
xmax = r1
ymax = r2
axmin = pi
axmax = 0
aymin = 3 * pi / 2
aymax = pi / 2
elif cos_angle < -1 + epsilon:
xmin = -r1
ymin = -r2
xmax = r1
ymax = r2
axmin = 0
axmax = pi
aymin = pi / 2
aymax = 3 * pi / 2
elif sin_angle > 1 - epsilon:
xmin = -r2
ymin = -r1
xmax = r2
ymax = r1
axmin = pi / 2
axmax = 3 * pi / 2
aymin = pi
aymax = 0
elif sin_angle < -1 + epsilon:
xmin = -r2
ymin = -r1
xmax = r2
ymax = r1
axmin = 3 * pi / 2
axmax = pi / 2
aymin = 0
aymax = pi
else:
tan_angle = sin_angle / cos_angle
axmax = atan(-r2 / r1 * tan_angle)
if axmax < 0:
axmax += twopi
xmax = (r1 * cos_angle * cos(axmax) - r2 * sin_angle * sin(axmax))
if xmax < 0:
xmax = -xmax
axmax = fmod(axmax + pi, twopi)
xmin = -xmax
axmin = fmod(axmax + pi, twopi)
aymax = atan(r2 / (r1 * tan_angle))
if aymax < 0:
aymax += twopi
ymax = (r1 * sin_angle * cos(aymax) + r2 * cos_angle * sin(aymax))
if ymax < 0:
ymax = -ymax
aymax = fmod(aymax + pi, twopi)
ymin = -ymax
aymin = fmod(aymax + pi, twopi)
if s < twopi - epsilon: # bb determined by the sector
def is_cyclic_ordered(x1, x2, x3):
return ((x1 < x2 and x2 < x3) or (x2 < x3 and x3 < x1)
or (x3 < x1 and x1 < x2))
x1 = cos_angle * r1 * cos(s1) - sin_angle * r2 * sin(s1)
x2 = cos_angle * r1 * cos(s2) - sin_angle * r2 * sin(s2)
y1 = sin_angle * r1 * cos(s1) + cos_angle * r2 * sin(s1)
y2 = sin_angle * r1 * cos(s2) + cos_angle * r2 * sin(s2)
if is_cyclic_ordered(s1, s2, axmin):
xmin = min(x1, x2)
if is_cyclic_ordered(s1, s2, aymin):
ymin = min(y1, y2)
if is_cyclic_ordered(s1, s2, axmax):
xmax = max(x1, x2)
if is_cyclic_ordered(s1, s2, aymax):
ymax = max(y1, y2)
return minmax_data([self.x + xmin, self.x + xmax],
[self.y + ymin, self.y + ymax],
dict=True)
